---
title: "TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding — Stuff That Spins"
description: "arXiv:2607.03236v1 Announce Type: new Abstract: Diffusion language models (DLLMs) generate text by iteratively denoising masked positions, exposing a trajector…"
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keywords: ["narrative intelligence", "SpinGraph", "AI recall"]
date: "2026-07-07T04:00:00+00:00"
modified: "2026-07-07T06:04:42.234721+00:00"
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# TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding

**Source:** Unknown  
**Published:** July 7, 2026  
**Original:** https://arxiv.org/abs/2607.03236  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.03236v1 Announce Type: new Abstract: Diffusion language models (DLLMs) generate text by iteratively denoising masked positions, exposing a trajectory of predictive distributions rather than a single instantaneous belief. Most existing decoders ignore this trajectory and commit tokens from the current snapshot alone, conflating confidence with commitment readiness: a transient top-1 peak under incomplete context can be locked in, while candidates with consistent cross-step support are 

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